After leading the company Boston Consulting GroupCompany’s 2023 report shows its IT advisors are more productive when using Open AI’s GPT-4 tool, the company received backlash that one should only Use ChatGPT for free instead of retaining his services for millions of dollars.
Here’s their reasoning: Consultants will get answers or advice from ChatGPT anyway, so they should avoid the third party and go straight to ChatGPT.
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There is a valuable lesson for anyone who is hiring or looking to be hired for AI-related jobs, be it as a developer, consultant or business user. The message of this critique is that anyone, even with limited or inadequate skills, can now use AI to get ahead or appear to be ahead. Because of this, the playing field has been leveled. People who can provide perspective and critical thinking to the information and results that AI provides are needed.
Even scientists, technologists and experts in the field can fall into the trap of relying too heavily on AI for output — instead of relying on their own expertise.
According to research on the subject, “AI solutions can also exploit our cognitive limitations, making us susceptible to illusions of understanding in which we believe we understand more about the world than we actually do.” published In essence.
Researchers Lisa Messer of Yale University and MJ Crockett of Princeton University warn that even scientists trained to evaluate information critically are attracted to machine-generated insights. go out.
Their study says: “Such illusions obscure the scientific community’s ability to see the formation of monolithic sciences, in which certain types of methods, questions and perspectives dominate alternative approaches, making science less creative and more error-prone.”
Messer and Crockett claim that in addition to concerns about AI ethics, bias, and job displacement, the risks of relying too heavily on AI as a source of expertise are only just beginning to become known.
In a mainstream business context, there are consequences to users relying too much on AI, from lost productivity to distrust. For example, users “can change, alter, and transform their actions to match AI recommendations,” Microsoft’s Samir Passi and Mihaela Vorvoreanu observed in a overview of research on the topic. Additionally, users will “have difficulty evaluating AI performance and understanding how AI impacts their decisions.”
That is the thought of Mai Maichief innovation officer at Esquire Bank, who sees AI as an important tool for engaging clients, while cautioning against using it as a substitute for human experience and critical thinking. Esquire Bank provides specialized finance to law firms and wants people who understand business and what AI can do to drive business. I recently met Mai at the Salesforce conference in New York, who shared his experience and perspective on AI.
Mai, who has risen through the ranks from programmer to multifaceted CIO, doesn’t think AI is likely to be one of the most valuable productivity tools on the horizon. But he also worries that relying too much on creative AI—whether for content or code—will diminish the quality and sharpness of human thinking.
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“We recognize that having great brains and great results is not necessarily as good as someone who is willing to think critically and form their own perspective on what AI and AI does for you under form of recommendations,” he said. “We want people who have the emotions and the self-awareness to say, ‘well, this doesn’t seem right, I’m brave enough to talk to someone, to make sure there’s a human being in the loop. repeat.'”
Esquire Bank is using Salesforce tools to embrace both sides of AI — generative and predictive. Predictive AI provides banking decision-makers with insights into “which lawyers are visiting their sites and helps personalize services based on these visits,” Mai, said the CIO role, which includes both customer engagement and IT systems.
As a fully virtual bank, Esquire uses its multiple AI systems across marketing teams, combining AI-generated content with predictive AI algorithms on the back end.
“Every person’s experience is different,” Mai says. “So we’re using AI to predict what content they’re going to get next. It’s based on all the analytics behind the scenes and in the system about what we can do with that particular prospect.”
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While working closely with AI, Mai discovered an interesting shift in human nature: People tend to ignore their own judgment and diligence as they increasingly rely on this system. “For example, we see that some people get lazy — they prompt something, then decide, ‘ah, that sounds like a really good response,’ and send it.”
When Mai senses the level of overreliance on AI, “I’ll take them into my office and say ‘I’m paying you for your perspective, not the prompts and feedback in AI that You made me read it. Just taking the results and giving them back to me is not what I expected, I expected your critical thinking.”
However, he still encourages members of his technology team to offload menial development tasks to AI-generated tools and platforms, and free up their time to work more closely with enterprise. “Programmers are finding that 60 percent of the time they used to spend writing was on administrative code that isn’t necessarily groundbreaking. AI can do it for them, through voice prompts. “
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As a result, he sees “the line between a classic programmer and a business analyst is blending more, because programmers don’t spend so much time doing things that don’t really add value.” increase. It also means that business analysts can become software developers.”
“It would be really cool if I could sit in front of a platform and say, ‘I want a system that can do this, this, this and this,’ and it does it.”
